Abstract. We develop a Bayesian approach to concept learning for crowdsourcing applications. A probabilistic belief over possible concept definitions is maintained and updated acc...
Paolo Viappiani, Sandra Zilles, Howard J. Hamilton...
Abstract--Feature selection is an important challenge in machine learning. Unfortunately, most methods for automating feature selection are designed for supervised learning tasks a...
We consider the problem of learning multiscale graphical models. Given a collection of variables along with covariance specifications for these variables, we introduce hidden var...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...
— This paper presents an analytical model for the analysis of Hybrid ARQ techniques on Discrete Time Markov Channels by means of Markov chains. The first contribution is an orig...
Modern malware often hide the malicious portion of their program code by making it appear as data at compiletime and transforming it back into executable code at runtime. This obf...
Paul Royal, Mitch Halpin, David Dagon, Robert Edmo...